Academic literature on the topic 'Artificial orthogonalization'

In order to obtain the environment’s information, cooperative robots could need a lot of sensors. A possible solution to reduce the number of sensors might be the use of control–observer structures. In this article, we have designed a control algorithm by using a modified hybrid computed torque method based on the principle of orthogonalization, but in order to avoid the use of tachometers in the implementation, we are including a velocity observer. The stability proof is developed by using the theory of Lyapunov. Simulation of the proposed control structure compared with a well-known control structure via the performance index analysis is presented. Experimental tests are implemented with the control structure that has the best performance index.

Here analytical and simulation results are presented characterizing the recoding arising when overlapping patterns of sensor input impinge on an array of model neurons with branched thresholded dendritic trees. Thus, the neural units employed are intended to capture the integrative behavior of pyramidal cells that sustain isolated Na+ or NMDA spikes in their branches. Given a defined set of sensor vectors, equations were derived for the probability of firing of both branches and neurons and for the expected overlap between the neural firing patterns triggered by two afferent patterns of given overlap. Thus, both the sparseness of the neural representation and the orthogonalization of overlapping vectors were computed. Simulations were then performed with an array of 1000 neurons comprising 30,000 branches to verify the analytical results and confirm their applicability to systems (which include any practicable artificial system) in which the combinatorically possible branches and neurons are severely subsampled. A means of readout and a measure of discrimination performance were provided so that the accuracy of discrimination among overlapping sensor vectors could be optimized as a function of neuron structure parameters. Good performance required both orthogonalization of the afferent patterns, so that discrimination was accurate and free of interference, and maintenance of a minimum level of neural activity, so that some neurons fired in response to each sensor pattern. It is shown that the discrimination performance achieved by arrays of neurons with branched dendritic trees could not be reached with single-compartment units, regardless of how many of the latter are used. The analytical results furnish a benchmark against which to measure further enhancements in the performance of subsequent simulated systems incorporating local neural mechanisms which, while often less amenable to closed-form analysis, are ubiquitous in biological neural circuitry.

The technological breakthrough in the form of Internet of Things (IoT), Big data and connected world is increasing the demand of better spectrum utilization. Half-Duplex (HD) transmission is mostly used in the earlier communication systems. The high transmission demand requires the better utilization of the existing spectrum. There are several possible ways to overcome the problem of better spectrum usage. In-Band Full Duplex (IBFD) is one of the techniques that can double the Spectral Efficiency (SE) in a Beyond 5G (B5G) communication system. In this paper, our aim is to use the spectral efficient IBFD scheme to improve the security of the system with minimum interference. The interference can be reduced by the addition of orthogonality between the transmitted and received signal of a relay. A component-forward scheme is proposed in this paper to create such orthogonality. For achieving the desired aim, IBFD is used with Device-to-Device (D2D), Artificial Noise (AN), Modulation based orthogonalization, Radio Frequency Energy Harvesting (RFEH) and proposed Full-Duplex Component Forward (FD-CF) algorithm for multiple relays. We also use non-linear harvested power as one of the sources to reuse the exiting power for evaluating the system performance. The derivation of Secrecy Outage Probability (SOP) and throughput is derived in this paper for the FD-CF cooperative communication and is explored with and without non-linear RFEH. The simulation results show the comparison between the component-forward and decode-and-forward communication with one or more relays.

There are many types and methods of simulation, but among them special attention should be paid to methods based on the theory of heuristic self-organization. All algorithms of the method of group argumentation (MGVA) are characterized by structural commonality on the principle of self-organization, which require insignificant requirements for a priori information to search for an infinite number of options. The advantage of the algorithm of the method of group consideration of arguments in comparison with other algorithms of this class is the presence of possibilities of expansion of the vector of initial data and the device for elimination of collinearity - reception of orthogonalization. MGVA consists of two blocks: pre-processing of observations taking into account the system of selected reference functions and calculation of selection applicants. As a result of the algorithm, models capable of controlling the process taking into account the phenomena accompanying a certain process are obtained. Given the commonality of the main provisions of the theory of self-organization of artificial neural networks and MGVA, the network variables are added to the model as a variable Z. As a result, we obtain a neural network that describes the physical phenomena accompanying the process. This will significantly increase the efficiency and accuracy of process management.

Дисертація на здобуття наукового ступеня кандидата технічних наук за спеціальністю 05.13.03 – системи та процеси керування. – Національний технічний університет "Харківський політехнічний інститут", Харків, 2018. Дисертація присвячена вирішенню актуальної науково-практичної задачі – розробці методів оптимального управління в умовах невизначеності. Показана можливість побудови адекватної математичної моделі індукційного дуплекс-процесу плавки як об'єкта управління в умовах неможливості реалізації плану активного експерименту в виробничих умовах. На основі цього запропоновано для опису кінцевого стану в задачі пошуку оптимального за кінцевим станом управління використовувати результати параметричного опису за визначенням локально-оптимальних значень вхідних змінних на основі реалізації процедури рідж-аналізу. Показано, як з використанням комбінованої процедури штучної ортогоналізації за даними пасивного експерименту при довільній формі плану експерименту і центрального ортогонального планування отримати таке параметричне опис. Розв'язана задача синтезу оптимального управління індукційної плавкою в печах ІСТ1 / 0.8-М5 в умовах альтернативних стратегій і доведено, що при виборі стратегії плавлення на "болоті" фазова траєкторія буде постійно змінюватися внаслідок корекції початкового стану, що обумовлено зміною швидкості розплавлення при обраному способі управління. Показано, як оптимальне за швидкодією управління може бути отримано з використанням принципу максимуму Понтрягіна в умовах обліку невизначеності в описі початкового стану об'єкта управління. Синтезований оптимальний регулятор температурного режиму в індукційної міксері на основі мультіальтернатівного опису кінцевого стану, характерною особливістю якого є використання оптимальних рішень рідж-аналізу і параметричної класифікації температурного режиму. Показано, що такий підхід може бути застосований для блоку логічних умов при логічному синтезі комбінованої системи управління індукційним дуплекс-процесом.
Thesis for the degree of candidate of technical sciences in specialty 05.13.03 – systems and control processes. – National Technical University "Kharkov Polytechnic Institute", Kharkov, 2018. The thesis is devoted to the solution of an actual scientific and practical problem – the development of optimal control methods in conditions of uncertainty. The possibility of building an adequate mathematical model of an induction duplex melting process as a control object under the conditions of impossibility of implementing an active experiment plan under production conditions is shown. Based on this, it is proposed to use the results of the parametric description by definition of the local-optimal values of the input variables based on the implementation of the ridge analysis procedure to describe the final state in the problem of finding the optimal by the final state control. It is shown how using a combined procedure of artificial orthogonalization according to a passive experiment with an arbitrary form of the experiment plan and central orthogonal planning to obtain such a parametric description. The problem of synthesizing optimal control of induction melting in IST1 / 0.8-M5 furnaces in terms of alternative strategies was solved and it was proved that when choosing a melting strategy in the “bog” phase trajectory will constantly change due to the correction of the initial state, which is caused by the change in melting rate with the selected control method. It is shown how the optimal in terms of speed control can be obtained using the Pontryagin maximum principle in terms of taking into account the uncertainty in the description of the initial state of the control object. An optimal temperature regulator was synthesized in an induction mixer based on a multi-alternative description of the final state, a characteristic feature of which is the use of optimal solutions of ridge analysis and parametric classification of the temperature regime. It is shown how such an approach can be applied to a block of logical conditions in the logical synthesis of a combined control system of an induction duplex process.

Дисертація на здобуття наукового ступеня кандидата технічних наук за спеціальністю 05.13.03 – системи та процеси керування. – Національний технічний університет "Харківський політехнічний інститут", Харків, 2018. Дисертація присвячена вирішенню актуальної науково-практичної задачі – розробці методів оптимального управління в умовах невизначеності. Показана можливість побудови адекватної математичної моделі індукційного дуплекс-процесу плавки як об'єкта управління в умовах неможливості реалізації плану активного експерименту в виробничих умовах. На основі цього запропоновано для опису кінцевого стану в задачі пошуку оптимального за кінцевим станом управління використовувати результати параметричного опису за визначенням локально-оптимальних значень вхідних змінних на основі реалізації процедури рідж-аналізу. Показано, як з використанням комбінованої процедури штучної ортогоналізації за даними пасивного експерименту при довільній формі плану експерименту і центрального ортогонального планування отримати таке параметричне опис. Розв'язана задача синтезу оптимального управління індукційної плавкою в печах ІСТ1 / 0.8-М5 в умовах альтернативних стратегій і доведено, що при виборі стратегії плавлення на "болоті" фазова траєкторія буде постійно змінюватися внаслідок корекції початкового стану, що обумовлено зміною швидкості розплавлення при обраному способі управління. Показано, як оптимальне за швидкодією управління може бути отримано з використанням принципу максимуму Понтрягіна в умовах обліку невизначеності в описі початкового стану об'єкта управління. Синтезований оптимальний регулятор температурного режиму в індукційної міксері на основі мультіальтернатівного опису кінцевого стану, характерною особливістю якого є використання оптимальних рішень рідж-аналізу і параметричної класифікації температурного режиму. Показано, що такий підхід може бути застосований для блоку логічних умов при логічному синтезі комбінованої системи управління індукційним дуплекс-процесом.
Thesis for the degree of candidate of technical sciences in specialty 05.13.03 – systems and control processes. – National Technical University "Kharkov Polytechnic Institute", Kharkov, 2018. The thesis is devoted to the solution of an actual scientific and practical problem – the development of optimal control methods in conditions of uncertainty. The possibility of building an adequate mathematical model of an induction duplex melting process as a control object under the conditions of impossibility of implementing an active experiment plan under production conditions is shown. Based on this, it is proposed to use the results of the parametric description by definition of the local-optimal values of the input variables based on the implementation of the ridge analysis procedure to describe the final state in the problem of finding the optimal by the final state control. It is shown how using a combined procedure of artificial orthogonalization according to a passive experiment with an arbitrary form of the experiment plan and central orthogonal planning to obtain such a parametric description. The problem of synthesizing optimal control of induction melting in IST1 / 0.8-M5 furnaces in terms of alternative strategies was solved and it was proved that when choosing a melting strategy in the "bog" phase trajectory will constantly change due to the correction of the initial state, which is caused by the change in melting rate with the selected control method. It is shown how the optimal in terms of speed control can be obtained using the Pontryagin maximum principle in terms of taking into account the uncertainty in the description of the initial state of the control object. An optimal temperature regulator was synthesized in an induction mixer based on a multi-alternative description of the final state, a characteristic feature of which is the use of optimal solutions of ridge analysis and parametric classification of the temperature regime. It is shown how such an approach can be applied to a block of logical conditions in the logical synthesis of a combined control system of an induction duplex process.

The Convolutional Neural Network (CNN) is a mathematical model designed to distill input information into a more useful representation. This distillation process removes information over time through a series of dimensionality reductions, which ultimately, grant the model the ability to resist noise, and generalize effectively. However, CNNs often contain elements that are ineffective at contributing towards useful representations. This Thesis aims at providing a remedy for this problem by introducing Absolute Cosine Value Regularization (ACVR). This is a regularization technique hypothesized to increase the representational power of CNNs by using a Gradient Descent Orthogonalization algorithm to force the vectors that constitute their filters at any given convolutional layer to occupy unique positions in Rⁿ. This method should in theory, lead to a more effective balance between information loss and representational power, ultimately, increasing network performance. The following Thesis proposes and examines the mathematics and intuition behind ACVR, and goes on to propose Dynamic-ACVR (D-ACVR). This Thesis also proposes and examines the effects of ACVR on the filters of a low-dimensional CNN, as well as the effects of ACVR and D-ACVR on traditional Convolutional filters in VGG-19. Finally, this Thesis proposes and examines regularization of the Pointwise filters in MobileNetv1.